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candidate should have a basic training at the Master’s level (similar to the 3 + 2 Bologna process and a total of 180+120 ECTS). However, applicants who hold a one- year Master’s degree may also be considered
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, processes, and practices, and how educational institutions prepare students to navigate these changes and contribute to the development and implementation of AI. The project may draw on perspectives from
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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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study pre-PhD. Development, teaching, and operation (40%) Contribute to our extensive portfolio of tasks linked to the ongoing digital transformation of the degree programs at Aarhus University
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: Expert knowledge on coupled 3D hydrodynamic-biogeochemical models and agent-based models Expert knowledge of marine physical- and biogeochemical processes in coastal and/or open waters Very good skills in
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universities. The transition towards electrified and energy-efficient energy systems poses significant challenges in predicting the coupled behaviour of thermofluid, electromagnetic, and rotordynamic processes
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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Procedure Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below. Please include: Motivated letter of application (max. one page) Project
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processes, feasibility testing, and health economic evaluation will be considered an advantage. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends